Type 2 diabetes mellitus (T2DM) and coronary artery disease (CAD) are leading causes of morbidity and mortality worldwide. Development of new and more effective approaches to prevention and treatment requires improved understanding of disease mechanisms. Genetic mapping in humans offers an approach to identify novel genes and DNA variants underlying the inherited contribution to disease susceptibility. Recently, we and others have used genome-wide association studies (GWAS) to identify novel genetic loci with strong association with blood lipid levels, CAD, and T2DM, along with a variety of related metabolic traits. Among the most intriguing of these loci is one on chromosome 7q32 that is just upstream of the KLF14 gene, which encodes a putative transcription factor. Although little is known of this gene's biology, single nucleotide polymorphisms (SNPs) in the locus are associated with high-density lipoprotein cholesterol (HDL-C), triglycerides, CAD, and T2DM. Expression quantitative trait locus (eQTL) studies in human adipose tissue have linked these same SNPs to the expression of ten genes that themselves harbor SNPs linked to a host of metabolic traits, including body mass index (BMI), fasting insulin levels, and fasting glucose levels. Based on these data, we hypothesize that KLF14 is a master regulator of the expression of a host of metabolic genes that together influence hyperglycemia, insulin resistance, obesity, blood lipid levels, and CAD-in other words, many of the cardinal features of the metabolic syndrome. We seek to test this hypothesis and better characterize the KLF14 molecular pathway. Building on our preliminary studies, we propose to use genome editing with cutting-edge clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) systems to knock out the KLF14 gene in human pluripotent stem cells, knock out the Klf14 gene in either the whole body or conditionally in metabolic tissues in mouse models, and knock in a FLAG tag into the endogenous KLF14 protein in mice with which to perform physiological ChIP experiments. We will use differentiated cells, primary tissues, and whole animals to comprehensively study the effects of KLF14 on gene expression and metabolic phenotypes. In doing this, we seek to establish a rapid and efficient multi-species approach with which to study the effects of metabolic genes discovered by gene mapping experiments.